Reading article tables Klandermans, Wood & Hughes, McAdam “High Risk” model.

Slides:



Advertisements
Similar presentations
The Regression Equation  A predicted value on the DV in the bi-variate case is found with the following formula: Ŷ = a + B (X1)
Advertisements

Quantitative Methods.
1 9. Logistic Regression ECON 251 Research Methods.
Statistics Measures of Regression and Prediction Intervals.
Logistic Regression and Odds Ratios
Multinomial Logistic Regression
Sociology 601 Class12: October 8, 2009 The Chi-Squared Test (8.2) – expected frequencies – calculating Chi-square – finding p When (not) to use Chi-squared.
Inferential Statistics  Hypothesis testing (relationship between 2 or more variables)  We want to make inferences from a sample to a population.  A.
Biol 500: basic statistics
Simple Correlation Scatterplots & r Interpreting r Outcomes vs. RH:
Independent Sample T-test Often used with experimental designs N subjects are randomly assigned to two groups (Control * Treatment). After treatment, the.
Multiple Regression – Basic Relationships
Chapter 7 Correlational Research Gay, Mills, and Airasian
Week 14 Chapter 16 – Partial Correlation and Multiple Regression and Correlation.
Hypothesis Testing. Outline The Null Hypothesis The Null Hypothesis Type I and Type II Error Type I and Type II Error Using Statistics to test the Null.
Elections and Voting It’s not just a right!.
Example of Simple and Multiple Regression
Beyond Bivariate: Exploring Multivariate Analysis.
LIS 570 Summarising and presenting data - Univariate analysis continued Bivariate analysis.
Wednesday PM  Presentation of AM results  Multiple linear regression Simultaneous Simultaneous Stepwise Stepwise Hierarchical Hierarchical  Logistic.
Bivariate Relationships Analyzing two variables at a time, usually the Independent & Dependent Variables Like one variable at a time, this can be done.
American Pride and Social Demographics J. Milburn, L. Swartz, M. Tottil, J. Palacio, A. Qiran, V. Sriqui, J. Dorsey, J. Kim University of Maryland, College.
Modeling Possibilities
Evidence-Based Medicine 3 More Knowledge and Skills for Critical Reading Karen E. Schetzina, MD, MPH.
Multiple Regression 1 Sociology 5811 Lecture 22 Copyright © 2005 by Evan Schofer Do not copy or distribute without permission.
Lesson Objectives: By the end of this lesson you will be able to: 1.Examine the problem of nonvoting in America. 2.Identify those people who typically.
Voters and Voter Behavior The Right to Vote. Voting Qualifications States must allow all people to vote who meet the minimum requirements set by the federal.
Regression. Regression  y= output, such as income, support for welfare  c= constant, does not change  b= coefficient (an increase of one year of education.
Chapter 6 Public Opinion, Political Socialization and Media.
Chi-square (χ 2 ) Fenster Chi-Square Chi-Square χ 2 Chi-Square χ 2 Tests of Statistical Significance for Nominal Level Data (Note: can also be used for.
DON’T TAKE NOTES! MUCH OF THE FOLLOWING IS IN THE COURSEPACK! Just follow the discussion and try to interpret the statistical results that follow.
The Introductory paper: The skeletal structure of the CAPPUN paper.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Interactions POL 242 Renan Levine March 13/15, 2007.
Week 5: Logistic regression analysis Overview Questions from last week What is logistic regression analysis? The mathematical model Interpreting the β.
Logistic Regression July 28, 2008 Ivan Katchanovski, Ph.D. POL 242Y-Y.
Preparing for the final - sample questions with answers.
SW388R6 Data Analysis and Computers I Slide 1 Multiple Regression Key Points about Multiple Regression Sample Homework Problem Solving the Problem with.
Solutions to Tutorial 5 Problems Source Sum of Squares df Mean Square F-test Regression Residual Total ANOVA Table Variable.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 13 Multiple Regression Section 13.3 Using Multiple Regression to Make Inferences.
Copyright © 2006 The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Dummy Variable Regression Models chapter ten.
SW318 Social Work Statistics Slide 1 Logistic Regression and Odds Ratios Example of Odds Ratio Using Relationship between Death Penalty and Race.
Welcome to Econ 420 Applied Regression Analysis Study Guide Week Seven.
Commonly Used Statistics in the Social Sciences Chi-square Correlation Multiple Regression T-tests ANOVAs.
 Relationship between education level, income, and length of time out of school  Our new regression equation: is the predicted value of the dependent.
Chapter 12 Confidence Intervals and Hypothesis Tests for Means © 2010 Pearson Education 1.
Testing the Differences between Means Statistics for Political Science Levin and Fox Chapter Seven 1.
Assignment In lab this week we will carry out all the analysis necessary for the assignment. You must take these results and write them up in the form.
Multiple Logistic Regression STAT E-150 Statistical Methods.
A study of the effects of divorce on parent-child relationships Nicole Cloutier and Krista Doucette.
The TITANIC In 1912 the luxury liner Titanic, on its first voyage across the Atlantic, struck an iceberg and sank. Some passengers got off the ship in.
Probability and odds Suppose we a frequency distribution for the variable “TB status” The probability of an individual having TB is frequencyRelative.
Multiple Regression David A. Kenny January 12, 2014.
Statistics Statistics Data measurement, probability and statistical tests.
Research Methodology Lecture No :26 (Hypothesis Testing – Relationship)
Cross Tabs and Chi-Squared Testing for a Relationship Between Nominal/Ordinal Variables.
Nonparametric Statistics
(Slides not created solely by me – the internet is a wonderful tool) SW388R7 Data Analysis & Compute rs II Slide 1.
Voters and Voter Behavior Chapter 6. Sect. 1 Section 1--The Constitution and the Right to Vote  1789 most states restricted the right to vote to white.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
RESEARCH METHODS Lecture 32. The parts of the table 1. Give each table a number. 2. Give each table a title. 3. Label the row and column variables, and.
Other tests of significance. Independent variables: continuous Dependent variable: continuous Correlation: Relationship between variables Regression:
Hypothesis Testing.
OTTFFSSENT ADGJM O{ne}T{wo}T{hree}F{our}F{ive}S{ix}, etc.
Chi-Square X2.
Multiple Regression.
Week 14 Chapter 16 – Partial Correlation and Multiple Regression and Correlation.
Collective Action Theory & Networks
Multiple logistic regression
Presentation transcript:

Reading article tables Klandermans, Wood & Hughes, McAdam “High Risk” model

Conditional probabilities.79 Klandermans & Oegema 1987

Klandermans & Oegema: Network Effects LinksNoneFormalInformalBoth % Participate0%7%24%19% Table suggests that informal links are most important!! Tilt of movement to educated, leftist, men came through networks, NOT opinions for/against movement

Klandermans & Oegema: Deciding to Go 1.Left parties, educated are key. Overlap with expect friends to go 2.Additional effect of believing Dutch government has effect 3.Majority who said they would go did not (6/10): cited specific “reasons”

Reading regression tables Look for symbols about “significance”, usually *’s. (Check footnotes, occasionally non-significant results are *’d.) Significant = effect too large to be due to chance. MORE SIGNIFICANT IS SMALLER P, p<.05 is significant, p<.001 is more significant. Look at sign of coefficient: + or -, and meaning of variables. [In a few cases, the coefficients are odds ratios instead, which are above 1.0 if effect is positive and below 1.0 if effect is negative.] Unstandardized “b” or “B” coefficients can be compared across equations for the same variables Standardized $ (beta) coefficients tell you how “strong” each variable is compared to others in the same equation.

Interpreting Klandermans & Oegema regression: DV=intend to go Equivalent to saying: LogOdds(Intend) =.04Age -.32Gender +.37Educ Voting –7.53 Numbers in parentheses are standard errors. Coefficients are significant when they are substantially larger than their standard error. Here, only education and voting for left parties are significant. Table SHOULD have labeled direction for gender, voting

Klandermans & Oegema: Deciding to Go 1.Left parties, educated are key. Overlap with expect friends to go 2.Additional effect of believing Dutch government has effect 3.Majority who said they would go did not (6/10): cited specific “reasons”

Reading Wood & Hughes Table B is undstandardized regression coefficient; gives equation for attitude toward pornography. The beta ( $ )column gives standardized coefficients. You can use it to find which independent variables are strongest. Here, age, then sex, then education. The t column is for a t-test, ratio of B to its standard error (not shown). The symbols show that all independent variables are significant.

Wood & Hughes Table Significant predictors are older, female (-male), -education, rural now & rural at 16, Southern manual or lower white collar occupation, came from low income family, not Black, Catholic & Conservative Protestant.

McAdam High Risk Activism